Integrating structure-based machine learning and co-evolution to investigate specificity in plant sesquiterpene synthases

Recent advances in lycopene and germacrene a biosynthesis and their role as antineoplastic drugs

Sesquiterpenes and tetraterpenes are classes of plant-derived natural products with antineoplastic effects. While plant extraction of the sesquiterpene, germacrene A, and the tetraterpene, lycopene suffers supply chain deficits and poor yields, chemical synthesis has difficulties in separating stereoisomers. This review highlights cutting-edge developments in producing germacrene A and lycopene from microbial cell factories. We then summarize the antineoplastic properties of β-elemene (a thermal product from germacrene A), sesquiterpene lactones (metabolic products from germacrene A), and lycopene. We also elaborate on strategies to optimize microbial-based germacrene A and lycopene production.

Catalytic Mechanism and Heterologous Biosynthesis Application of Sesquiterpene Synthases

Sesquiterpenes comprise a diverse group of natural products with a wide range of applications in cosmetics, food, medicine, agriculture, and biofuels. Heterologous biosynthesis is increasingly employed for sesquiterpene production, aiming to overcome the limitations associated with chemical synthesis and natural extraction. Sesquiterpene synthases (STSs) play a crucial role in the heterologous biosynthesis of sesquiterpene. Under the catalysis of STSs, over 300 skeletons are produced through various cyclization processes (C1-C10 closure, C1-C11 closure, C1-C6 closure, and C1-C7 closure), which are responsible for the diversity of sesquiterpenes. According to the cyclization types, we gave an overview of advances in understanding the mechanism of STSs cyclization from the aspects of protein crystal structures and site-directed mutagenesis. We also summarized the applications of engineering STSs in the heterologous biosynthesis of sesquiterpene. Finally, the bottlenecks and potential research directions related to the STSs cyclization mechanism and application of modified STSs were presented.

Sequence-Structure Analysis Unlocking the Potential Functional Application of the Local 3D Motifs of Plant-Derived Diterpene Synthases

Plant-derived diterpene synthases (PdiTPSs) play a critical role in the formation of structurally and functionally diverse diterpenoids. However, the specificity or functional-related features of PdiTPSs are not well understood. For a more profound insight, we collected, constructed, and curated 199 functionally characterized PdiTPSs and their corresponding 3D structures. The complex correlations among their sequences, domains, structures, and corresponding products were comprehensively analyzed. Ultimately, our focus narrowed to the geometric arrangement of local structures. We found that local structural alignment can rapidly localize product-specific residues that have been validated by mutagenesis experiments. Based on the 3D motifs derived from the residues around the substrate, we successfully searched diterpene synthases (diTPSs) from the predicted terpene synthases and newly characterized PdiTPSs, suggesting that the identified 3D motifs can serve as distinctive signatures in diTPSs (I and II class). Local structural analysis revealed the PdiTPSs with more conserved amino acid residues show features unique to class I and class II, whereas those with fewer conserved amino acid residues typically exhibit product diversity and specificity. These results provide an attractive method for discovering novel or functionally equivalent enzymes and probing the product specificity in cases where enzyme characterization is limited.

Decoding Catalysis by Terpene Synthases

The review by Christianson, published in 2017 on the twentieth anniversary of the emergence of the field, summarizes the foundational discoveries and key advances in terpene synthase/cyclase (TS) biocatalysis (Christianson, D. W. Chem Rev2017, 117 (17), 11570-11648. DOI: 10.1021/acs.chemrev.7b00287). Here, we review the TS literature published since then, bringing the field up to date and looking forward to what could be the near future of TS rational design. Many revealing discoveries have been made in recent years, building on the knowledge and fundamental principles uncovered during those initial two decades of study. We use these to explore TS reaction chemistry and see how a combined experimental and computational approach helps to decipher the complexities of TS catalysis. Revealed are a suite of catalytic motifs which control product outcome in TSs, some obvious, some more subtle. We examine each in detail, using the most recent papers and insights to illustrate how exactly this fascinating class of enzymes takes a single acyclic substrate and turns it into the many thousands of complex terpenoids found in Nature. We then explore some of the recent strategies for TS engineering, including machine learning and other data-driven approaches. From this, rational and predictive engineering of TSs, "designer terpene synthases", will begin to emerge as a realistic goal.

Plant terpene specialized metabolism: complex networks or simple linear pathways?

From the perspectives of pathway evolution, discovery and engineering of plant specialized metabolism, the nature of the biosynthetic routes represents a critical aspect. Classical models depict biosynthesis typically from an end-point angle and as linear, for example, connecting central and specialized metabolism. As the number of functionally elucidated routes increased, the enzymatic foundation of complex plant chemistries became increasingly well understood. The perception of linear pathway models has been severely challenged. With a focus on plant terpenoid specialized metabolism, we review here illustrative examples supporting that plants have evolved complex networks driving chemical diversification. The completion of several diterpene, sesquiterpene and monoterpene routes shows complex formation of scaffolds and their subsequent functionalization. These networks show that branch points, including multiple sub-routes, mean that metabolic grids are the rule rather than the exception. This concept presents significant implications for biotechnological production.

Biosynthesis of monoterpenoid and sesquiterpenoid as natural flavors and fragrances

Terpenoids are a large class of plant-derived compounds, that constitute the main components of essential oils and are widely used as natural flavors and fragrances. The biosynthesis approach presents a promising alternative route in terpenoid production compared to plant extraction or chemical synthesis. In the past decade, the production of terpenoids using biotechnology has attracted broad attention from both academia and the industry. With the growing market of flavor and fragrance, the production of terpenoids directed by synthetic biology shows great potential in promoting future market prospects. Here, we reviewed the latest advances in terpenoid biosynthesis. The engineering strategies for biosynthetic terpenoids were systematically summarized from the enzyme, metabolic, and cellular dimensions. Additionally, we analyzed the key challenges from laboratory production to scalable production, such as key enzyme improvement, terpenoid toxicity, and volatility loss. To provide comprehensive technical guidance, we collected milestone examples of biosynthetic mono- and sesquiterpenoids, compared the current application status of chemical synthesis and biosynthesis in terpenoid production, and discussed the cost drivers based on the data of techno-economic assessment. It is expected to provide critical insights into developing translational research of terpenoid biomanufacturing.

Predicting functions of putative fungal sesquiterpene synthase genes based on multiomics data analysis

Sesquiterpenes (STs) are secondary metabolites, which mediate biotic interactions between different organisms. Predicting the species-specific ST repertoires can contribute to deciphering the language of communication between organisms of the same or different species. High biochemical plasticity and catalytic promiscuity of sesquiterpene synthases (STSs), however, challenge the homology-based prediction of the STS functions. Using integrated analyses of genomic, transcriptomic, volatilomic, and metabolomic data, we predict product profiles for 116 out of 146 putative STS genes identified in the genomes of 30 fungal species from different trophic groups. Our prediction method is based on the observation that STSs encoded by genes closely related phylogenetically are likely to share the initial enzymatic reactions of the ST biosynthesis pathways and, therefore, produce STs via the same reaction route. The classification by reaction routes allows to assign STs known to be emitted by a particular species to the putative STS genes from this species. Gene expression information helps to further specify these ST-to-STS assignments. Validation of the computational predictions of the STS functions using both in silico and experimental approaches shows that integrated multiomic analyses are able to correctly link cyclic STs of non-cadalane type to genes. In the process of the experimental validation, we characterized catalytic properties of several putative STS genes from the mycorrhizal fungus Laccaria bicolor. We show that the STSs encoded by the L.bicolor mycorrhiza-induced genes emit either nerolidol or α-cuprenene and α-cuparene, and discuss the possible roles of these STs in the mycorrhiza formation.

Beyond sequence: Structure-based machine learning

Recent breakthroughs in protein structure prediction demarcate the start of a new era in structural bioinformatics. Combined with various advances in experimental structure determination and the uninterrupted pace at which new structures are published, this promises an age in which protein structure information is as prevalent and ubiquitous as sequence. Machine learning in protein bioinformatics has been dominated by sequence-based methods, but this is now changing to make use of the deluge of rich structural information as input. Machine learning methods making use of structures are scattered across literature and cover a number of different applications and scopes; while some try to address questions and tasks within a single protein family, others aim to capture characteristics across all available proteins. In this review, we look at the variety of structure-based machine learning approaches, how structures can be used as input, and typical applications of these approaches in protein biology. We also discuss current challenges and opportunities in this all-important and increasingly popular field.

Sesquiterpenoids Isolated from the Rhizomes of Genus Atractylodes

Atractylodes plants have been used in traditional herbal medicine to treat gastrointestinal diseases and contain various chemical compounds. Sesquiterpenoids are the most important therapeutic compounds in Atractylodes rhizomes. Based on studies reported from 2000 to 2022, we classified sesquiterpenoids by their chemical skeletons and original resources. Moreover, we discussed their biosynthesis and physicochemical and pharmacological features. We reported sesquiterpenoids with skeletal moieties, such as monocyclic sesquiterpenes (bisabolene- and elemene-type), bicyclic sesquiterpenes (eudesmane-, isopterocarpolone-, hydroxycarissone-, eremophilane-, bisesquiterpenoid-, guaiane- and spirovetivane-type and eudesmane lactones) and tricyclic sesquiterpenes (cyperene- and patchoulene-type), with their biosynthetic pathways, chemical modifications and in vivo metabolites. The pharmacological activities of sesquiterpenoids as anti-inflammatory, anti-tumor, anti-diabetic and anti-microbial and for treating gastrointestinal disorders have been reported for this genus.

How a 10-epi-Cubebol Synthase Avoids Premature Reaction Quenching to Form a Tricyclic Product at High Purity

Terpenes are the largest class of natural products and are attractive targets in the fuel, fragrance, pharmaceutical, and flavor industries. Harvesting terpenes from natural sources is environmentally intensive and often gives low yields and purities, requiring further downstream processing. Engineered terpene synthases (TSs) offer a solution to these problems, but the low sequence identity and high promiscuity among TSs are major challenges for targeted engineering. Rational design of TSs requires identification of key structural and chemical motifs that steer product outcomes. Producing the sesquiterpenoid 10-epi-cubebol from farnesyl pyrophosphate (FPP) requires many steps and some of Nature’s most difficult chemistry. 10-epi-Cubebol synthase from Sorangium cellulosum (ScCubS) guides a highly reactive carbocationic substrate through this pathway, preventing early quenching and ensuring correct stereochemistry at every stage. The cyclizations carried out by ScCubS potentially represent significant evolutionary expansions in the chemical space accessible by TSs. Here, we present the high-resolution crystal structure of ScCubS in complex with both a trinuclear magnesium cluster and pyrophosphate. Computational modeling, experiment, and bioinformatic analysis identified residues important in steering the reaction chemistry. We show that S206 is crucial in 10-epi-cubebol synthesis by enlisting the nearby F211 to shape the active site contour and prevent the formation of early escape cadalane products. We also show that N327 and F104 control the distribution between several early-stage cations and whether the final product is derived from the germacrane, cadalane, or cubebane hydrocarbon scaffold. Using these insights, we reengineered ScCubS so that its main product was germacradien-4-ol, which derives from the germacrane, rather than the cubebane, scaffold. Our work emphasizes that mechanistic understanding of cation stabilization in TSs can be used to guide catalytic outcomes.

Predictive Engineering of Class I Terpene Synthases Using Experimental and Computational Approaches

Terpenoids are a highly diverse group of natural products with considerable industrial interest. Increasingly, engineered microbes are used for the production of terpenoids to replace natural extracts and chemical synthesis. Terpene synthases (TSs) show a high level of functional plasticity and are responsible for the vast structural diversity observed in natural terpenoids. Their relatively inert active sites guide intrinsically reactive linear carbocation intermediates along one of many cyclisation paths via exertion of subtle steric and electrostatic control. Due to the absence of a strong protein interaction with these intermediates, there is a remarkable lack of sequence‐function relationship within the TS family, making product‐outcome predictions from sequences alone challenging. This, in combination with the fact that many TSs produce multiple products from a single substrate hampers the design and use of TSs in the biomanufacturing of terpenoids. This review highlights recent advances in genome mining, computational modelling, high‐throughput screening, and machine‐learning that will allow more predictive engineering of these fascinating enzymes in the near future.